Study options
- Starting in
- September 2025
- Location
- Mile End
- Fees
- Home: £15,250
Overseas: £33,500
EU/EEA/Swiss students
What you'll study
The programme has three pillars: i) supply chain and logistics management in practice, ii) data science methods to better capture uncertainty, and 3) operations research and management science to optimise decisions. For the first pillar, you'll learn the fundamental processes and decisions involved in logistics and supply chain management, together with the business context in which they are embedded. These include, for instance, demand forecasting and management, inventory management, transportation, quality management, warehouse management, supply network design, and production planning. You will become familiar with various factors that are challenging and reshaping existing supply and logistics networks, including sustainability, digitalisation, artificial intelligence, and changes in the geopolitical landscape. The second pillar focuses on transforming big data produced by firms, their partners, and the broader production networks to economic, environmental, and social value. For this, you will learn statistics and machine learning and develop projects to solve logistics and supply chain problems using the methods of data analytics. The third pillar enables moving from predictive to prescriptive analytics by using the modern methods of management science and operations research, which enables optimising decisions at operational, strategic, and tactical levels.
The programme has an interdisciplinary perspective, integrating knowledge from business studies, management science, and data science, with a core focus on logistics and supply chain management. We provide a comprehensive education on these topics that is delivered across three semesters. A number of elective modules allow you to specialise on international business strategy, complex networks and innovation, and project management.
Structure
- Nine compulsory modules
- Choose one elective module
- One Capstone project module
Compulsory/Core modules
Python is a language with a simple syntax, and a powerful set of libraries. While it is easy for beginners to learn, it is widely used in many scientific areas including data science, machine learning and blockchain. This module is an introduction to the Python programming language for students without prior programming experience. Topics include algorithms and problem solving, data types, control structures, functions, arrays, files, and the mechanics of running, testing, and debugging.
This module will provide an introduction to the methods and the tools of data science. The module will use the programming language Python and will cover the fundamental stages of data analysis workflow, including data collection, data pre-processing, exploratory analysis, statistical modelling, and business reporting. This will involve web scraping, merging and cleaning data sets, feature engineering, descriptive analysis and data visualisation, and applying various unsupervised and supervised machine learning models. The module will focus on applications in the general business management domain as well as the analysis of digital currency and blockchain data.
This is the capstone module for the MSc Supply Chain and Logistics Analytics, for which students will work on projects and use analytical methods to solve a problem related to contemporary issues that concern supply chains, logistics networks, or transportation. The projects can be based on real-world data, simulated data, or a theoretical mathematical model. The projects and problems can be supplied by firms (subject to arrangements), sourced from online data repositories, or identified from the academic literature. Students will present preliminary results as a group to an audience consisting of supervisors and problem owners. The assessment of the Group Work component (30%) will incorporate peer assessment. The final assessment of the module will be based on individual project reports that cover specific aspects of the project.
This module introduces students to supply chain and operations management, including its purpose, general principles, and relationships with other functional areas of businesses. It is also intended to introduce standard terms, concepts, and metrics,crucial for understanding and analysing supply chains and interacting with business professionals. Topics include contemporary issues in supply chain, logistics, and transportation; supply chain drivers and metrics; supply chain strategy and network design; levels of planning; planning and coordinating demand and supply; production planning and inventory control process; and quality management. We will look at case studies on the use of supply chain and operations analysis in practice.
Sustainable supply chain management is core to mitigating the detrimental impacts of global production, distribution, and consumption. In this module, we introduce and discuss the fundamentals of environmental analytics for supply chains, by integrating academic knowledge and industry practice and including case studies. We first discuss the different methods and systems for measuring and reporting environmental impact, including Life Cycle Assessment, carbon footprint, water footprint, nonrenewable materials management, and environmental reporting. We then discuss circular economy and associated supply chain strategies and business models, including reverse logistics and closed loop supply chains. We then focus on operational initiatives, such as green inventory management, responsible purchasing, green technology choice, and eco-design. We finally look at the social pillar of sustainability and discuss social responsibility and slavery in supply chains, highlighting the relationships and potential conflicts with the environmental pillar.
This module introduces the students to Management Science, which is the study of advanced analytical and computational methods to support effective and informed managerial decision-making. The principal idea in Management Science is to formulate managerial decision problems as mathematical problems, which can subsequently be solved with mathematical or numerical techniques. The use of these methods will be illustrated with applications in diverse disciplines, in relation to supply chain and logistics management. Topics include linear and nonlinear programming, integer programming, network models, decision analysis, and queuing analysis.
Effective supply chain planning and control is the driver of efficiency, flexibility, robustness, and resilience in supply chains. This module will focus on models and techniques required for designing, planning, managing, and controlling supply chain operations. The module will consider decisions and processes at different levels in the decision making hierarchy. Topics include supply network design, aggregate production planning, MPS, MRP, and ERP, JIT systems, inventory management models, production scheduling, and quality management. Students will also learn about fundamental aspects of corporate / enterprise information systems designed to support planning and control.
In this module, we discuss the current trends and analytical frontiers in supply chain management. We have a particular focus on technological innovations that are transforming and restructuring supply chains, including Industry 4.0, IoT, blockchain and other traceability solutions, big data, and robotics. We will discuss the applications of advanced operations research, machine learning, data science, and network science methods, particularly in such data-rich and digital environments. The module will combine reading of academic literature, discussion of case studies, investigation of industrial projects and initiatives, and industry guest lectures.
In today's global supply chains, manufactured products often travel across multiple countries and multiple states, using multiple modes of transportation, before reaching final customers. Along the way, these products are processed at a variety of inventory transfer points, and reconfigured and combined with other products with the goal of arriving intact at the right place and right time. Topics covered include logistics strategy, transportation infrastructure, transport modes, logistics modelling, warehouse operations, logistics outsourcing, and green logistics.
The process of business forecasting involves the study of historical data to discover their underlying tendencies and patterns and the use of this knowledge to project the data into future time periods. This is a challenging task with non-stationarity in data and the impact of external economic factors. The topics covered include simple and multiple regression, time series decomposition and analysis, exponential smoothing, auto-regressive and moving average models, willingness to pay/demand estimation and pricing, dynamic pricing, and quantity-based revenue management.
This 0-credit module covers Mathematics and Statistics topics which are useful for the different quantitative modules and MSc dissertations. The Mathematics topics include: linear and non linear equations, differentiation, growth and discounting and logarithms. The Statistics topics include: descriptive statistics, probabilities and distributions.
Elective modules
The module aims to introduce students to concepts and practices related to managing in a globally volatile, complex, dynamic environment within which organisations, national and international institutions and individuals interact. The elective is designed to be an advanced global strategic management course presenting material that is highly contemporary. This course provides balanced global strategic insights along with proven practical business frameworks and prepares you to respond quickly to today's challenging global environment.
The structure and dynamics of various complex networks (e.g. World Wide Web, online social, intra/interorganisational, im/export trade networks) are examined. A unified theoretical framework to analyse sociologically relevant phenomena exhibiting complex dynamic network structures (e.g. information diffusion, cultural fads, financial crises, and viral marketing) is the aim. Innovation, to uncover the structural foundations of knowledge creation, transfer, sharing, and diffusion in various empirical domains is emphasised from an interdisciplinary perspective by combining current research on complex networks with contributions from relevant organisational and sociological research.
The module will focus on project management techniques, methodologies, theories appropriate to projects that deliver complex outcomes in a context of high uncertainty on the desired result. The module will also provide team and teaming management principles and practices needed to obtain the desired project management results within time, budget and quality. Students will be encouraged to take advantage of opportunities to earn an accreditation for project management and the course will prepare students for this additional examination.
Python is a language with a simple syntax, and a powerful set of libraries. While it is easy for beginners to learn, it is widely used in many scientific areas including data science, machine learning and blockchain. This module is an introduction to the Python programming language for students without prior programming experience. Topics include algorithms and problem solving, data types, control structures, functions, arrays, files, and the mechanics of running, testing, and debugging.
This module is an introduction to cryptocurrency and blockchain programming for students without prior programming experience of building a blockchain. Students will learn key fundamentals of blockchain technologies and theories behind cryptocurrency transactions as well as practical training of creation of their own blockchains. Topics include how to build a blockchain, how to create a cryptocurrency, and how to create a smart contract. Although this module is not highly technical, it requires a basic level of mathematics and Python knowledge.
Assessment
Modules are assessed through a combination of essays, individual and group projects, presentations, and exams.
Teaching
Teaching will be delivered by research-intensive staff who will critically evaluate and integrate professional knowledge of the subject material into their teaching. The theoretical teaching will be enriched by guest lectures and projects from the logistics industry and supply chain functions of firms. You will develop a critical and comprehensive knowledge of the modern tools of analytics and the professional practice of logistics and supply chain management. We follow an interdisciplinary, analytics-focused, and hands-on approach to teaching.
You’ll be assigned an Academic Advisor who will guide and support you in both academic and pastoral matters, throughout your course. Our lecturers also publicise their office hours, when they are available to give feedback and advice on coursework, on their online staff profiles.
Where you'll learn
Facilities
- ThinkPod interactive collaboration space with presentation, recording and video conferencing facilities.
- School of Business and Management's resources, including industry-standard datasets and accounting tools.
- 24-hour library on campus.
Campus
Teaching is based at Queen Mary’s main Mile End campus, one of the largest self-contained residential campuses in the capital. Our location in the heart of London’s East End offers a rich cultural environment.
We have invested £105m in new facilities over the past five years to offer our students an exceptional learning environment. Recent developments include the £39m Graduate Centre, providing 7,700 square metres of learning and teaching space.
The campus is 15 minutes from Central London by tube, where you will have access to many of the University of London’s facilities, including the Senate House library.
You’ll be studying in the financial capital of the world, close to London's main financial districts - the Square Mile and Canary Wharf.
About the School
School of Business and Management
The School of Business and Management has a reputation as a socially engaged management school, with an innovative, multidisciplinary, mindful and responsible approach. We invite our students to ask incisive questions, to challenge their assumptions, and to search for solutions to real-world challenges.
We ensure students experience innovative and engaging educational pathways, alongside supportive staff and excellent research facilities.
The School is accredited by the Association to Advance Collegiate Schools of Business (AACSB), which ensures that the highest standards of excellence in teaching, research, curriculum, and learner success are met.
In the most recent Research Excellence Framework (REF 2021), the School of Business and Management dramatically moved up the Times Higher Education rankings. Among 108 UK business schools, the School now ranks:
- 22nd for overall research quality (up from 39th in REF2014)
- 28th for research outputs (up from 34th)
- 12th for research impact (up from 24th)
- 21st for research environment (up from 59th)
Queen Mary is also part of the Russell Group - a body of leading UK universities dedicated to research and teaching excellence.
Career paths
- This course could lead to specialised roles, such as: Supply Chain Analyst, Supply Chain Planner, Supply Chain Manager, Logistics Planner, Operations Manager, Production Planner, Demand Planner, Supply Chain Consultant, as well as general analytics roles such as Business Analyst, Data Scientist, and Decision Scientist.
- The combination of practical and theoretical knowledge would lend itself well to students who wish to start their own businesses in the logistics and supply chain management area.
- You will leave with academic knowledge that would be well desired in a PhD in this field.
Fees and funding
Full-time study
September 2025 | 1 year
- Home: £15,250
- Overseas: £33,500
EU/EEA/Swiss students
Conditional deposit
Home: Not applicable
Overseas: £2000
Information about deposits
Queen Mary alumni can get a £1000, 10% or 20% discount on their fees depending on the programme of study. Find out more about the Alumni Loyalty Award
Funding
There are a number of ways you can fund your postgraduate degree.
- Scholarships and bursaries
- Postgraduate loans (UK students)
- Country-specific scholarships for international students
Our Advice and Counselling service offers specialist support on financial issues, which you can access as soon as you apply for a place at Queen Mary. Before you apply, you can access our funding guides and advice on managing your money:
Entry requirements
UK
Degree requirements
A 2:1 or above at undergraduate level in in any subject, provided the degree contains satisfactory study of Mathematics and Statistics. Subjects likely to contain sufficient quantitative elements include Accounting, Mathematics, Sciences, Engineering, Computer Science, Economics and Finance.
Additional information
Students from less quantitatively oriented degrees, such as Management and Politics, are welcome if they have focused on the more quantitative elements of those degrees.
Find out more about how to apply for our postgraduate taught courses.
International
English language requirements
The English language requirements for our programmes are indicated by English bands, and therefore the specific test and score acceptable is based on the band assigned to the academic department within which your chosen course of study is administered. Note that for some academic departments there are programmes with non-standard English language requirements.
The English Language requirements for entry to postgraduate taught in the School of Business and Management falls within the following English band:
Band 4: IELTS (Academic) minimum score 6.5 overall with 6.0 in each of Writing, Listening, Reading and Speaking
We accept a range of English tests and qualifications categorised in our English bands for you to demonstrate your level of English Language proficiency. See all accepted English tests that we deem equivalent to these IELTS scores.
Visas and immigration
Find out how to apply for a student visa.